ArticleBMC medicine2015
Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement.
Article in BMC medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 944 papers, 12 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Validation of Non-invasive Risk Models for Prediction of Incident Type 2 Diabetes in a Swedish Population
Spectral and Ultra High Resolution CT Systems for Non-Invasive Detection of Myocardial Ischemia: Stress CT Perfusion VS. FFR-CT
Who cites it
944 citing papers in PubMed, 12 syntheses or guidelines pooled it, 1,896 citations in OpenAlex.
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- Machine Learning-Based Prognostic Models for Functional Outcomes in Spinal Cord Injury: Systematic Review.JMIR medical informatics · 2026Pooled it
- Characteristics of Cardiovascular Disease Prediction Models Considering Mental Disorders: A Systematic Review.Journal of the American Heart Association · 2026Pooled it
- Prediction models for early detection and diagnosis of lung cancer in people who have never smoked: a systematic review and critical appraisal.Cancer causes & control : CCC · 2026Pooled it
- Artificial Intelligence in Physical, Occupational and Neuro-Rehabilitation: Clinical Effectiveness, Prognostic Performance, and Pre-Implementation Feasibility - A Systematic Review.Journal of medical systems · 2026Pooled it
- Diagnostic Performance of Artificial Intelligence in Detecting and Distinguishing Pancreatic Ductal Adenocarcinoma via Computed Tomography: A Systematic Review and Meta-Analysis.Journal of imaging informatics in medicine · 2026Pooled it
- Prognostic models for all-cause and cardiovascular mortality in type 2 diabetes: Systematic review.Diabetic medicine : a journal of the British Diabetic Association · 2026Pooled it
- Application of type 2 inflammation-related biomarkers in risk prediction models for acute exacerbations in adult asthma: a systematic review.Frontiers in medicine · 2026Pooled it
- Optimizing Intubation Prediction in Pneumonia Patients: A Systematic Review and Meta-Analysis of Machine Learning Algorithms.Pulmonary medicine · 2026Pooled it
- Comparison of machine learning methods versus traditional Cox regression for survival prediction in cancer using real-world data: a systematic literature review and meta-analysis.BMC medical research methodology · 2025Pooled it
- Methodological and applicability pitfalls of clinical prediction models for asthma diagnosis: a systematic review and critical appraisal of evidence.BMC medical research methodology · 2025Pooled it
- Development and Validation of an Ipsilateral Breast Tumor Recurrence Risk Estimation Tool Incorporating Real-World Data and Evidence From Meta-Analyses: A Retrospective Multicenter Cohort Study.JCO clinical cancer informatics · 2025Pooled it
- Lower baseline scores best predict achievement of the minimal clinically important difference after hip arthroscopy: A machine learning analysis from the Femoroacetabular Impingement RandomiSed Controlled Trial and embedded prospective cohort.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Trial
- A simplified nomogram for predicting deep vein thrombosis: development in NHANES and retrospective single-center external validation.Annals of medicine · 2026Article
- Real-world evidence on off-label underdosing of direct oral anticoagulants in Asian patients with atrial fibrillation: prescribing patterns, determinants, and outcomes.Future science OA · 2026Article
- Development and internal validation of a nomogram for predicting postoperative bone nonunion in infectious spondylitis: a retrospective cohort study.Annals of medicine · 2026Article
- Post-SABR early PSA density kinetics in androgen deprivation therapy-naïve patients: early landmark models for long-term biochemical recurrence-free survival.Clinical and translational radiation oncology · 2026Article
- Pragmatic Screening for Sarcopenia in Non-Small Cell Lung Cancer: Development and Internal Validation of a Prospective Risk Model Integrating T12 CT Indices and Routine Clinical Variables.Cancer medicine · 2026Article
- Clarifying Methodological Considerations in the Evaluation of Dev-NSRAS for Neonatal Pressure Injury Risk.Journal of clinical nursing · 2026Article
- A Machine Learning-Derived Risk Scorecard for Pneumonia Hospitalization in Japanese Old-Old Adults.Geriatrics & gerontology international · 2026Article
884 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.